

    \filetitle{litterman}{Litterman's prior dummy observations for BVARs}{BVAR/litterman}

	\paragraph{Syntax}\label{syntax}

\begin{verbatim}
O = BVAR.litterman(Rho,Mu,Lmb)
\end{verbatim}

\paragraph{Input arguments}\label{input-arguments}

\begin{itemize}
\item
  \texttt{Rho} {[} numeric {]} - White-noise priors (\texttt{Rho = 0})
  or random-walk priors (\texttt{Rho = 1}).
\item
  \texttt{Mu} {[} numeric {]} - Weight on the dummy observations.
\item
  \texttt{Lmb} {[} numeric {]} - Exponential increase in weight
  depending on the lag; \texttt{Lmb = 0} means all lags are weighted
  equally.
\end{itemize}

\paragraph{Output arguments}\label{output-arguments}

\begin{itemize}
\itemsep1pt\parskip0pt\parsep0pt
\item
  \texttt{O} {[} bvarobj {]} - BVAR object that can be passed into the
  \href{VAR/estimate}{\texttt{VAR/estimate}} function.
\end{itemize}

\paragraph{Description}\label{description}

See the section explaining the \href{BVAR/Contents}{weights on prior
dummies}, i.e.~the input argument \texttt{Mu}.

\paragraph{Example}\label{example}


